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Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal ne...

Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal ne...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e5dc0a3207cc4c9ba3552310cd89836b

Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal neuromorphic hardware

About this item

Full title

Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal neuromorphic hardware

Publisher

London: Nature Publishing Group UK

Journal title

Nature communications, 2025-01, Vol.16 (1), p.243-15, Article 243

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Mixed signal analog/digital neuromorphic circuits represent an ideal medium for reproducing bio-physically realistic dynamics of biological neural systems in real-time. However, similar to their biological counterparts, these circuits have limited resolution and are affected by a high degree of variability. By developing a recurrent spiking neural...

Alternative Titles

Full title

Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal neuromorphic hardware

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_e5dc0a3207cc4c9ba3552310cd89836b

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e5dc0a3207cc4c9ba3552310cd89836b

Other Identifiers

ISSN

2041-1723

E-ISSN

2041-1723

DOI

10.1038/s41467-024-55749-y

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